30-second-Update 100-m-Mesh Data Assimilation Experiments: A Sudden Local Rain Case in Kobe on 11 September 2014

DOI Web Site 被引用文献11件 参考文献32件 オープンアクセス
  • Maejima Yasumitsu
    RIKEN Advanced Institute for Computational Science (AICS)
  • Kunii Masaru
    RIKEN Advanced Institute for Computational Science (AICS) Meteorological Research Institute, Japan Meteorological Agency
  • Miyoshi Takemasa
    RIKEN Advanced Institute for Computational Science (AICS) University of Maryland, College Park Japan Agency for Marine-Earth Science and Technology

書誌事項

公開日
2017
DOI
  • 10.2151/sola.2017-032
公開者
公益社団法人 日本気象学会

説明

<p>This study aims to investigate the impacts of 30-second-update and 100-m-resolution data assimilation (DA) on a prediction of sudden local torrential rains caused by an isolated convective system in Kobe city on 11 September 2014. We perform a Local Ensemble Transform Kalman filter (LETKF) experiment with the Japan Meteorological Agency non-hydrostatic model (JMA-NHM) at 1-km and 100-m resolution using every-30-second radar reflectivity observed by the phased array weather radar (PAWR) at Osaka University. The 1-km-mesh experiment shows that 30-second-update PAWR DA has positive impacts on the analyses and forecasts. Moreover, the 100-m-mesh experiment shows significant advantages in representing the rainfall intensity and fine structure of the convective system. The promising results suggest that 30-second-update, 100-m-mesh DA have a great potential for predicting sudden local rain events.</p>

収録刊行物

  • SOLA

    SOLA 13 (0), 174-180, 2017

    公益社団法人 日本気象学会

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参考文献 (32)*注記

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